_base_ = './base_nwpuv2.py'
# model settings
model = dict(
    type='WeakRCNN',
    backbone=dict(
        type='ReResNet',
        depth=50,
        num_stages=4,
        out_indices=(0, 1, 2, 3),
        frozen_stages=1,
        style='pytorch',
        init_cfg=dict(
            type='Pretrained',
            checkpoint='../_PACKAGE/re_resnet50_c8_batch256-25b16846.pth')),

#     pretrained=None,
#     backbone=dict(type='VGG16'),
#     neck=None,    
    neck=dict(
        type='ReFPN',
        in_channels=[256, 512, 1024, 2048],
        out_channels=256,
        start_level=1,#从backbone提取的特征第n个stage开始输入fpn
        end_level=2,
        num_outs=1),#输出的个数是1
    roi_head=dict(
        type='OICRRoIHead',
        bbox_roi_extractor=dict(
            type='SingleRoIExtractor',
            roi_layer=dict(type='RoIPool', output_size=7),
            out_channels=512,
            featmap_strides=[8]),
        bbox_head=dict(
            type='RES_OICRHead',
            in_channels=256,#用resnet50作为backbone，in_channels为1024
            hidden_channels=4096,
            roi_feat_size=7,
            num_classes=10))
)
img_norm_cfg = dict(
    mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)
work_dir = 'work_dirs/oicr_reresnet50/'
